diff --git a/.github/citation/citation.json b/.github/citation/citation.json index 658a96b..c57bd1a 100644 --- a/.github/citation/citation.json +++ b/.github/citation/citation.json @@ -1 +1 @@ -{"Harnessing Deep Neural Networks with Logic Rules": {"citation": 781, "last update": "2024-11-05"}, "Deep Learning with Logical Constraints": {"citation": 70, "last update": "2024-11-05"}, "A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints": {"citation": 8, "last update": "2024-11-05"}, "Hyper-class Augmented and Regularized Deep Learning for Fine-grained Image Classification": {"citation": 236, "last update": "2024-11-05"}, "Injecting Logical Constraints into Neural Networks via Straight-Through Estimators": {"citation": 24, "last update": "2024-11-05"}, "Rewriting a Deep Generative Model": {"citation": 132, "last update": "2024-11-05"}, "DeepProbLog: Neural Probabilistic Logic Programming": {"citation": 634, "last update": "2024-11-05"}, "Guided Open Vocabulary Image Captioning with Constrained Beam Search": {"citation": 261, "last update": "2024-11-06"}, "DeepEdit: Knowledge Editing as Decoding with Constraints": {"citation": 15, "last update": "2024-11-06"}, "Don't Pour Cereal into Coffee: Differentiable Temporal Logic for Temporal Action Segmentation": {"citation": 27, "last update": "2024-11-06"}, "VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images": {"citation": 249, "last update": "2024-11-06"}, "MultiplexNet: Towards Fully Satisfied Logical Constraints in Neural Networks": {"citation": 57, "last update": "2024-11-06"}, "Interpretability Beyond Feature Attribution:Quantitative Testing with Concept Activation Vectors (TCAV)": {"citation": 2080, "last update": "2024-11-06"}, "Label-free Concept Bottleneck Models": {"citation": 121, "last update": "2024-11-06"}, "Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification": {"citation": 160, "last update": "2024-11-06"}, "Editing a classifier by rewriting its prediction rules": {"citation": 80, "last update": "2024-11-06"}, "Concept Bottleneck Models": {"citation": 802, "last update": "2024-11-06"}, "Interactive Concept Bottleneck Models": {"citation": 48, "last update": "2024-11-06"}, "Promises and Pitfalls of Black-Box Concept Learning Models": {"citation": 83, "last update": "2024-11-06"}, "Addressing Leakage in Concept Bottleneck Models": {"citation": 58, "last update": "2024-11-06"}, "CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning": {"citation": 359, "last update": "2024-11-06"}, "POST-HOC CONCEPT BOTTLENECK MODELS": {"citation": 184, "last update": "2024-11-06"}, "Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat": {"citation": 9, "last update": "2024-11-06"}, "A Semantic Loss Function for Deep Learning with Symbolic Knowledge": {"citation": 551, "last update": "2024-11-06"}, "Neurologic decoding:(un) supervised neural text generation with predicate logic constraints": {"citation": 131, "last update": "2024-11-06"}, "A review of some techniques for inclusion of domain-knowledge into deep neural networks": {"citation": 154, "last update": "2024-11-06"}, "Informed machine learning-a taxonomy and survey of integrating prior knowledge into learning systems": {"citation": 793, "last update": "2024-11-06"}, "The Connectionist Inductive Learning and Logic Programming System": {"citation": 254, "last update": "2024-11-06"}} \ No newline at end of file +{"Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat": {"citation": 9, "last update": "2024-11-06"}, "A Semantic Loss Function for Deep Learning with Symbolic Knowledge": {"citation": 551, "last update": "2024-11-06"}, "Neurologic decoding:(un) supervised neural text generation with predicate logic constraints": {"citation": 131, "last update": "2024-11-06"}, "A review of some techniques for inclusion of domain-knowledge into deep neural networks": {"citation": 154, "last update": "2024-11-06"}, "Informed machine learning-a taxonomy and survey of integrating prior knowledge into learning systems": {"citation": 793, "last update": "2024-11-06"}, "The Connectionist Inductive Learning and Logic Programming System": {"citation": 254, "last update": "2024-11-06"}, "Harnessing Deep Neural Networks with Logic Rules": {"citation": 781, "last update": "2024-11-08"}, "Deep Learning with Logical Constraints": {"citation": 70, "last update": "2024-11-08"}, "A Pseudo-Semantic Loss for Autoregressive Models with Logical Constraints": {"citation": 8, "last update": "2024-11-08"}, "Hyper-class Augmented and Regularized Deep Learning for Fine-grained Image Classification": {"citation": 236, "last update": "2024-11-08"}, "Injecting Logical Constraints into Neural Networks via Straight-Through Estimators": {"citation": 24, "last update": "2024-11-08"}, "Rewriting a Deep Generative Model": {"citation": 133, "last update": "2024-11-08"}, "DeepProbLog: Neural Probabilistic Logic Programming": {"citation": 635, "last update": "2024-11-08"}, "Guided Open Vocabulary Image Captioning with Constrained Beam Search": {"citation": 261, "last update": "2024-11-08"}, "DeepEdit: Knowledge Editing as Decoding with Constraints": {"citation": 15, "last update": "2024-11-08"}, "Don't Pour Cereal into Coffee: Differentiable Temporal Logic for Temporal Action Segmentation": {"citation": 27, "last update": "2024-11-08"}, "VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images": {"citation": 251, "last update": "2024-11-08"}, "MultiplexNet: Towards Fully Satisfied Logical Constraints in Neural Networks": {"citation": 57, "last update": "2024-11-08"}, "Interpretability Beyond Feature Attribution:Quantitative Testing with Concept Activation Vectors (TCAV)": {"citation": 2086, "last update": "2024-11-08"}, "Label-free Concept Bottleneck Models": {"citation": 122, "last update": "2024-11-08"}, "Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification": {"citation": 165, "last update": "2024-11-08"}, "Editing a classifier by rewriting its prediction rules": {"citation": 81, "last update": "2024-11-08"}, "Concept Bottleneck Models": {"citation": 808, "last update": "2024-11-08"}, "Interactive Concept Bottleneck Models": {"citation": 48, "last update": "2024-11-08"}, "Promises and Pitfalls of Black-Box Concept Learning Models": {"citation": 83, "last update": "2024-11-08"}, "Addressing Leakage in Concept Bottleneck Models": {"citation": 58, "last update": "2024-11-08"}, "CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning": {"citation": 359, "last update": "2024-11-08"}, "POST-HOC CONCEPT BOTTLENECK MODELS": {"citation": 187, "last update": "2024-11-08"}} \ No newline at end of file diff --git a/README.md b/README.md index b6b8329..34c60a7 100644 --- a/README.md +++ b/README.md @@ -20,7 +20,7 @@ A list of awesome resources related to constraint learning | Venue | Title | Affiliation |       Link       |   Source   | | :---: | :---: | :---------: | :---: | :----: | |EMNLP 2020|CommonGen: A Constrained Text Generation Challenge for Generative Commonsense Reasoning|USC| [[paper]](https://arxiv.org/pdf/1911.03705.pdf)![Scholar citations](https://img.shields.io/badge/Citations-359-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/INK-USC/CommonGen)![GitHub stars](https://img.shields.io/github/stars/INK-USC/CommonGen.svg?logo=github&label=Stars)| -|Medical image analysis 2021|VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images|Technical University of Munich| [[paper]](https://arxiv.org/abs/2001.09193)![Scholar citations](https://img.shields.io/badge/Citations-249-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/anjany/verse)![GitHub stars](https://img.shields.io/github/stars/anjany/verse.svg?logo=github&label=Stars)| +|Medical image analysis 2021|VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images|Technical University of Munich| [[paper]](https://arxiv.org/abs/2001.09193)![Scholar citations](https://img.shields.io/badge/Citations-251-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/anjany/verse)![GitHub stars](https://img.shields.io/github/stars/anjany/verse.svg?logo=github&label=Stars)| ### Data Augmentation | Venue | Title | Affiliation |       Link       |   Source   | | :---: | :---: | :---------: | :---: | :----: | @@ -36,16 +36,16 @@ A list of awesome resources related to constraint learning |EMNLP 2017|Guided Open Vocabulary Image Captioning with Constrained Beam Search|The Australian National University| [[paper]](https://aclanthology.org/D17-1098.pdf)![Scholar citations](https://img.shields.io/badge/Citations-261-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/nocaps-org/updown-baseline)![GitHub stars](https://img.shields.io/github/stars/nocaps-org/updown-baseline.svg?logo=github&label=Stars)| |NIPS 2022|Don't Pour Cereal into Coffee: Differentiable Temporal Logic for Temporal Action Segmentation|NUS| [[paper]](https://diff-tl.github.io/assets/docs/dtl_neurips2022.pdf)![Scholar citations](https://img.shields.io/badge/Citations-27-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/ZiweiXU/DTL-action-segmentation)![GitHub stars](https://img.shields.io/github/stars/ZiweiXU/DTL-action-segmentation.svg?logo=github&label=Stars)| |AAAI 2021|MultiplexNet: Towards Fully Satisfied Logical Constraints in Neural Networks|University of Edinburgh| [[paper]](https://arxiv.org/pdf/2111.01564.pdf)![Scholar citations](https://img.shields.io/badge/Citations-57-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/NickHoernle/semantic_loss)![GitHub stars](https://img.shields.io/github/stars/NickHoernle/semantic_loss.svg?logo=github&label=Stars)| -|NIPS 2018|DeepProbLog: Neural Probabilistic Logic Programming|KU Leuven| [[paper]](https://arxiv.org/pdf/1805.10872.pdf)![Scholar citations](https://img.shields.io/badge/Citations-634-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/ML-KULeuven/deepproblog)![GitHub stars](https://img.shields.io/github/stars/ML-KULeuven/deepproblog.svg?logo=github&label=Stars)| +|NIPS 2018|DeepProbLog: Neural Probabilistic Logic Programming|KU Leuven| [[paper]](https://arxiv.org/pdf/1805.10872.pdf)![Scholar citations](https://img.shields.io/badge/Citations-635-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/ML-KULeuven/deepproblog)![GitHub stars](https://img.shields.io/github/stars/ML-KULeuven/deepproblog.svg?logo=github&label=Stars)| |ICML 2022|Injecting Logical Constraints into Neural Networks via Straight-Through Estimators|Arizona State University| [[paper]](https://arxiv.org/pdf/2307.04347.pdf)![Scholar citations](https://img.shields.io/badge/Citations-24-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/azreasoners/cl-ste)![GitHub stars](https://img.shields.io/github/stars/azreasoners/cl-ste.svg?logo=github&label=Stars)| ### Concept bottleneck models | Venue | Title | Affiliation |       Link       |   Source   | | :---: | :---: | :---------: | :---: | :----: | -|ICML 2020|Concept Bottleneck Models|Standard University| [[paper]](https://arxiv.org/pdf/2007.04612.pdf)![Scholar citations](https://img.shields.io/badge/Citations-802-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/yewsiang/ConceptBottleneck)![GitHub stars](https://img.shields.io/github/stars/yewsiang/ConceptBottleneck.svg?logo=github&label=Stars)| -|ICLR 2023|POST-HOC CONCEPT BOTTLENECK MODELS|Standard University| [[paper]](https://arxiv.org/pdf/2205.15480.pdf)![Scholar citations](https://img.shields.io/badge/Citations-184-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/mertyg/post-hoc-cbm)![GitHub stars](https://img.shields.io/github/stars/mertyg/post-hoc-cbm.svg?logo=github&label=Stars)| +|ICML 2020|Concept Bottleneck Models|Standard University| [[paper]](https://arxiv.org/pdf/2007.04612.pdf)![Scholar citations](https://img.shields.io/badge/Citations-808-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/yewsiang/ConceptBottleneck)![GitHub stars](https://img.shields.io/github/stars/yewsiang/ConceptBottleneck.svg?logo=github&label=Stars)| +|ICLR 2023|POST-HOC CONCEPT BOTTLENECK MODELS|Standard University| [[paper]](https://arxiv.org/pdf/2205.15480.pdf)![Scholar citations](https://img.shields.io/badge/Citations-187-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/mertyg/post-hoc-cbm)![GitHub stars](https://img.shields.io/github/stars/mertyg/post-hoc-cbm.svg?logo=github&label=Stars)| |ICML 2023|Dividing and Conquering a BlackBox to a Mixture of Interpretable Models: Route, Interpret, Repeat|BU| [[paper]](https://arxiv.org/pdf/2307.05350.pdf)![Scholar citations](https://img.shields.io/badge/Citations-9-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/batmanlab/ICML-2023-Route-interpret-repeat)![GitHub stars](https://img.shields.io/github/stars/batmanlab/ICML-2023-Route-interpret-repeat.svg?logo=github&label=Stars)| -|CVPR 2023|Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification|UPENN| [[paper]](https://openaccess.thecvf.com/content/CVPR2023/papers/Yang_Language_in_a_Bottle_Language_Model_Guided_Concept_Bottlenecks_for_CVPR_2023_paper.pdf)![Scholar citations](https://img.shields.io/badge/Citations-160-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/YueYANG1996/LaBo)![GitHub stars](https://img.shields.io/github/stars/YueYANG1996/LaBo.svg?logo=github&label=Stars)| -|ICLR 2023|Label-free Concept Bottleneck Models|UCSD| [[paper]](https://openreview.net/pdf?id=FlCg47MNvBA)![Scholar citations](https://img.shields.io/badge/Citations-121-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/Trustworthy-ML-Lab/Label-free-CBM)![GitHub stars](https://img.shields.io/github/stars/Trustworthy-ML-Lab/Label-free-CBM.svg?logo=github&label=Stars)| +|CVPR 2023|Language in a Bottle: Language Model Guided Concept Bottlenecks for Interpretable Image Classification|UPENN| [[paper]](https://openaccess.thecvf.com/content/CVPR2023/papers/Yang_Language_in_a_Bottle_Language_Model_Guided_Concept_Bottlenecks_for_CVPR_2023_paper.pdf)![Scholar citations](https://img.shields.io/badge/Citations-165-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/YueYANG1996/LaBo)![GitHub stars](https://img.shields.io/github/stars/YueYANG1996/LaBo.svg?logo=github&label=Stars)| +|ICLR 2023|Label-free Concept Bottleneck Models|UCSD| [[paper]](https://openreview.net/pdf?id=FlCg47MNvBA)![Scholar citations](https://img.shields.io/badge/Citations-122-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/Trustworthy-ML-Lab/Label-free-CBM)![GitHub stars](https://img.shields.io/github/stars/Trustworthy-ML-Lab/Label-free-CBM.svg?logo=github&label=Stars)| |AAAI 2023|Interactive Concept Bottleneck Models|Google| [[paper]](https://arxiv.org/pdf/2212.07430.pdf)![Scholar citations](https://img.shields.io/badge/Citations-48-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/google-research/google-research/tree/master/interactive_cbms)| |NIPS 2022|Addressing Leakage in Concept Bottleneck Models|Harvard University| [[paper]](https://finale.seas.harvard.edu/sites/scholar.harvard.edu/files/finale/files/10494_addressing_leakage_in_concept_.pdf)![Scholar citations](https://img.shields.io/badge/Citations-58-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/dtak/addressing-leakage)![GitHub stars](https://img.shields.io/github/stars/dtak/addressing-leakage.svg?logo=github&label=Stars)| |ICML 2021|Promises and Pitfalls of Black-Box Concept Learning Models|Harvard University| [[paper]](https://arxiv.org/pdf/2106.13314.pdf)![Scholar citations](https://img.shields.io/badge/Citations-83-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)|| @@ -53,6 +53,6 @@ A list of awesome resources related to constraint learning ### Model Editing | Venue | Title | Affiliation |       Link       |   Source   | | :---: | :---: | :---------: | :---: | :----: | -|ECCV 2020|Rewriting a Deep Generative Model|MIT| [[paper]](https://arxiv.org/pdf/2007.15646.pdf)![Scholar citations](https://img.shields.io/badge/Citations-132-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/davidbau/rewriting)![GitHub stars](https://img.shields.io/github/stars/davidbau/rewriting.svg?logo=github&label=Stars)| -|NIPS 2021|Editing a classifier by rewriting its prediction rules|MIT| [[paper]](https://proceedings.neurips.cc/paper/2021/file/c46489a2d5a9a9ecfc53b17610926ddd-Paper.pdf)![Scholar citations](https://img.shields.io/badge/Citations-80-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/MadryLab/EditingClassifiers)![GitHub stars](https://img.shields.io/github/stars/MadryLab/EditingClassifiers.svg?logo=github&label=Stars)| +|ECCV 2020|Rewriting a Deep Generative Model|MIT| [[paper]](https://arxiv.org/pdf/2007.15646.pdf)![Scholar citations](https://img.shields.io/badge/Citations-133-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/davidbau/rewriting)![GitHub stars](https://img.shields.io/github/stars/davidbau/rewriting.svg?logo=github&label=Stars)| +|NIPS 2021|Editing a classifier by rewriting its prediction rules|MIT| [[paper]](https://proceedings.neurips.cc/paper/2021/file/c46489a2d5a9a9ecfc53b17610926ddd-Paper.pdf)![Scholar citations](https://img.shields.io/badge/Citations-81-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/MadryLab/EditingClassifiers)![GitHub stars](https://img.shields.io/github/stars/MadryLab/EditingClassifiers.svg?logo=github&label=Stars)| |arxiv 2024|DeepEdit: Knowledge Editing as Decoding with Constraints|UCLA| [[paper]](https://arxiv.org/pdf/2401.10471.pdf)![Scholar citations](https://img.shields.io/badge/Citations-15-_.svg?logo=google-scholar&labelColor=4f4f4f&color=3388ee)| [[code]](https://github.com/wangywUST/DeepEdit)![GitHub stars](https://img.shields.io/github/stars/wangywUST/DeepEdit.svg?logo=github&label=Stars)|